12,912 research outputs found

    `Sinking' in a bed of grains activated by shearing

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    We show how a weak force, ff, enables intruder motion through dense granular materials subject to external mechanical excitations, in the present case stepwise shearing. A force acts on a Teflon disc in a two dimensional system of photoelastic discs. This force is much smaller than the smallest force needed to move the disc without any external excitation. In a cycle, material + intruder are sheared quasi-statically from γ=0\gamma = 0 to γmax\gamma_{max}, and then backwards to γ=0\gamma = 0. During various cycle phases, fragile and jammed states form. Net intruder motion, δ\delta, occurs during fragile periods generated by shear reversals. δ\delta per cycle, e.g. the quasistatic rate cc, is constant, linearly dependent on γmax\gamma_{max} and ff. It vanishes as, c(ϕcϕ)ac \propto (\phi_c - \phi)^a, with a3a \simeq 3 and ϕcϕJ\phi_c \simeq \phi_J, reflecting the stiffening of granular systems under shear as ϕϕJ\phi \rightarrow \phi_J. The intruder motion induces large scale grain circulation. In the intruder frame, this motion is a granular analogue to fluid flow past a cylinder, where ff is the drag force exerted by the flow.Comment: 4 pages, 5 figures letter with supplementarie

    Revisiting the BB-physics anomalies in RR-parity violating MSSM

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    In recent years, several deviations from the Standard Model predictions in semileptonic decays of BB-meson might suggest the existence of new physics which would break the lepton-flavour universality. In this work, we have explored the possibility of using muon sneutrinos and right-handed sbottoms to solve these BB-physics anomalies simultaneously in RR-parity violating minimal supersymmetric standard model. We find that the photonic penguin induced by exchanging sneutrino can provide sizable lepton flavour universal contribution due to the existence of logarithmic enhancement for the first time. This prompts us to use the two-parameter scenario (C9V,C9U)(C^{\rm V}_9, \, C^{\rm U}_9) to explain bs+b \to s \ell^+ \ell^- anomaly. Finally, the numerical analyses show that the muon sneutrinos and right-handed sbottoms can explain bs+b \to s \ell^+ \ell^- and R(D())R(D^{(\ast)}) anomalies simultaneously, and satisfy the constraints of other related processes, such as BK()ννˉB \to K^{(\ast)} \nu \bar\nu decays, BsBˉsB_s-\bar B_s mixing, ZZ decays, as well as D0μ+μD^0 \to \mu^+ \mu^-, τμρ0\tau \to \mu \rho^0, BτνB \to \tau \nu, DsτνD_s \to \tau \nu, τKν\tau \to K \nu, τμγ\tau \to \mu \gamma, and τμμμ\tau \to \mu\mu\mu decays.Comment: 10 pages, 8 figures, matches to the version published in EPJ

    Optical spectroscopy study on CeTe3_3: evidence for multiple charge-density-wave orders

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    We performed optical spectroscopy measurement on single crystal of CeTe3_3, a rare-earth element tri-telluride charge density wave (CDW) compound. The optical spectra are found to display very strong temperature dependence. Besides a large and pronounced CDW energy gap being present already at room temperature as observed in earlier studies, the present measurement revealed the formation of another energy gap at smaller energy scale at low temperature. The second CDW gap removes the electrons near EF_F which undergo stronger scattering. The study yields evidence for the presence of multiple CDW orders or strong fluctuations in the light rare-earth element tri-telluride.Comment: 5 figure

    Physics-informed Neural Network Combined with Characteristic-Based Split for Solving Navier-Stokes Equations

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    In this paper, physics-informed neural network (PINN) based on characteristic-based split (CBS) is proposed, which can be used to solve the time-dependent Navier-Stokes equations (N-S equations). In this method, The output parameters and corresponding losses are separated, so the weights between output parameters are not considered. Not all partial derivatives participate in gradient backpropagation, and the remaining terms will be reused.Therefore, compared with traditional PINN, this method is a rapid version. Here, labeled data, physical constraints and network outputs are regarded as priori information, and the residuals of the N-S equations are regarded as posteriori information. So this method can deal with both data-driven and data-free problems. As a result, it can solve the special form of compressible N-S equations -- -Shallow-Water equations, and incompressible N-S equations. As boundary conditions are known, this method only needs the flow field information at a certain time to restore the past and future flow field information. We solve the progress of a solitary wave onto a shelving beach and the dispersion of the hot water in the flow, which show this method's potential in the marine engineering. We also use incompressible equations with exact solutions to prove this method's correctness and universality. We find that PINN needs more strict boundary conditions to solve the N-S equation, because it has no computational boundary compared with the finite element method
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